… A biometric quality assessment method was embedded in … First, we report the performance
of the deep models in terms of … For this particular experiment, we changed the set up in a way …

… scaling up and scaling down to see if there is any significant change between the results. As
we can see by scaling up, the performance … Face recognition technology and the embedded …

… in order to speed up label generation, we used an extensive … to pre-process our set X of
training samples; each image has been … networks for large-scale image recognition,’’ 2014, arXiv:…

… ; in order to evaluate the performance in real environments, we … This dataset was originally
gathered for face recognition, but it is … for embedded systems, even though it does not directly …

… evaluate the performance of different face recognition models, … up a series of baselines
under the proposed FRUITS protocols. In Tab.9, we illustrate different face recognition systems …

… detection, face detection, the military, medical image analysis, intelligent transporation systems,
crowd detection… -based embedded platforms and a quantitative performance comparison …

… Due to the insufficiency of this technical, facial recognition systems were often reported
with unstable performance or … To sum up, we present FR modules and their commonly-used …

… performance over the state-ofthe-art (SoTA) on four datasets (IJB… ’s age or make-up. These
parameter settings make the … -pose face recognition in unconstrained environments. Beijing …

… achieve realtime performance when running on embedded systems. … optimize our detection
network model, including reducing memory usage and increasing network computing speed. …

… in devising facial recognition algorithms and systems, but to … the performance evaluation of
our improved face recognition … multiple face recognition using deep learning on embedded …